Biography

Dr. Makonin received a Ph.D. degree in computing science from Simon Fraser University (SFU), Burnaby, Canada, in 2014. He is an Adjunct Professor in the School of Engineering Science and the Principal Investigator of the Computational Sustainability Lab at Simon Fraser University (SFU). He also has the position of Head Instructor at SFU’s Big Data Hub, where he teaches data science and machine learning courses. He is a registered Professional Engineering (P.Eng.) with EGBC and has been a software engineer for over 25 years. Stephen is a Senior Member of the IEEE. He currently sits on the IEEE DataPort Advisory Committee, serves as the Editor in Chief of the IEEE DataPort Metadata Review Board, and serves as an Editorial Board Member of Nature’s Scientific Data journal. Additionally, he is the Vice-Chair of the Big Data Governance and Metadata Management (BDGMM, P2957).

Publications (Peer-Reviewed) [Citation data from Google Scholar]

Power/Energy Engineering & Smart Grid

1. Bundit Buddhahai, Stephen Makonin.
   A Nonintrusive Load Monitoring Based on Multi-Target Regression Approach.
   IEEE Access, vol. 9, pp. 163033-163042 (2021).
2. Alon Harell, Richard Jones, Stephen Makonin, Ivan V. Bajic.
   TraceGAN: Synthesizing Appliance Power Signatures Using Generative Adversarial Networks.
   IEEE Transactions on Smart Grid, vol. 12, no. 5, pp. 4553-4563 (2021).
3. Md. Zulfiquar Ali Bhotto, Richard Jones, Stephen Makonin, Ivan V. Bajic.
   Short-Term Demand Prediction Using an Ensemble of Linearly-Constrained Estimators.
   IEEE Transactions on Power Systems, vol. 36, no. 4, pp. 3163-3175 (2021).
4. Christoph Klemenjak, Stephen Makonin, Wilfried Elmenreich.
   Investigating the performance gap between testing on real and denoised aggregates in non-intrusive load monitoring.
   Energy Informatics, vol. 4, 3. 5, pp. 1-15 (2021).
5. Richard Jones, Christoph Klemenjak, Stephen Makonin, Ivan V. Bajic.
   Stop! Exploring Bayesian Surprise to Better Train NILM.
   Proceedings of the 5th International Workshop on Non- Intrusive Load Monitoring, 2020.
6. Shikha Singh, Angshul Majumdar, Stephen Makonin.
   Compressive Non-Intrusive Load Monitoring.
   Proceedings of the 7th ACM International Conference on Systems for Energy-Efficient Built Environments (BuildSys), 2020.
7. Chinthaka Dinesh, Stephen Makonin, Ivan V. Bajic.
   Residential Power Forecasting Based on Affinity Aggregation Spectral Clustering.
   IEEE Access, vol. 8, pp. 99431-99444 (2020).
8. Richard Jones, Alejandro Rodriguez-Silva, Stephen Makonin.
   Increasing the Accuracy and Speed of Universal Non-Intrusive Load Monitoring (UNILM) Using a Novel Real-Time Steady-State Block Filter.
   Proceedings of the 11th Conference on Innovative Smart Grid Technologies (ISGT), 2020.
9. Christoph Klemenjak, Stephen Makonin, Wilfried Elmenreich.
   Towards Comparability in Non-Intrusive Load Monitoring: On Data and Performance Evaluation.
   Proceedings of the 11th Conference on Innovative Smart Grid Technologies (ISGT), 2020.
10. Christoph Klemenjak, Anthony Faustine, Stephen Makonin, Wilfried Elmenreich.
    On metrics to assess the transferability of machine learning models in non-intrusive load monitoring.
    arXiv preprint arXiv:1912.06200, 2019.
11. Megha Gaur, Stephen Makonin, Ivan V. Bajic, Angshul Majumdar.
    Performance evaluation of techniques for identifying abnormal energy consumption in buildings.
    IEEE Access, vol. 7, pp. 62721-62733 (2019).
12. Alejandro Rodriguez-Silva, Stephen Makonin.
    Universal Non-Intrusive Load Monitoring (UNILM) Using Filter Pipelines, Probabilistic Knapsack, and Labelled Partition Maps.
    Proceedings of the 11th IEEE PES Asia-Pacific Power and Energy Engineering Conference 2019 (APPEEC), 2019.
13. Alon Harell, Stephen Makonin, Ivan V. Bajic.
    WaveNILM: A Causal Neural Network for Power Disaggregation from the Complex Power Signal.
    Proceedings of the 44th International Conference on Acoustics, Speech, and Signal Processing (ICASSP), pp. 8335-8339, 2019.
14. Chinthaka Dinesh, Stephen Makonin, Ivan V. Bajic.
    Residential Power Forecasting Using Load Identification and Graph Spectral Clustering.
    IEEE Transactions on Circuits and Systems II: Express Briefs, vol. 66, no. 11 , pp. 1900-1904 (2019).
15. Alon Harell, Stephen Makonin, Ivan V. Bajic.
    A Recurrent Neural Network for Multisensory Non-Intrusive Load Monitoring on a Raspberry Pi.
    Proceedings of the IEEE 20th International Workshop on Multimedia Signal Processing (MMSP), 2018.
16. Chinthaka Dinesh, Stephen Makonin, Ivan V. Bajic.
    Incorporating Time-Of-Day Usage Patterns Into Non-Intrusive Load Monitoring.
    Proceedings of the 5th IEEE Global Conference on Signal and Information Processing (GlobalSIP), 2017.
17. Chinthaka Dinesh, Stephen Makonin, Ivan V. Bajic.
    Understanding Appliance Power Consumption Without Sensors.
    In Poster Session at the 3rd Annual IC-IMPACTS Research Conference, 2017.
    
18. Md. Zulfiquar Ali Bhotto, Stephen Makonin, Ivan V. Bajic.
    Load disaggregation based on aided linear integer programming.
    IEEE Transactions on Circuits and Systems II: Express Briefs, vol. 64, no. 7, pp. 792-796 (2016).
19. Stephen Makonin.
    Investigating the Switch Continuity Principle Assumed in Non-Intrusive Load Monitoring (NILM).
    Proceedings of the 29th Annual IEEE Canadian Conference on Electrical and Computer Engineering (CCECE), 2016.
20. Stephen Makonin, Fred Popowich, Ivan V. Bajic, Bob Gill, Lyn Bartram.
    Exploiting HMM Sparsity to Perform Online Real-Time Nonintrusive Load Monitoring.
    IEEE Transactions on Smart Grid, vol. 7, no. 6, pp. 2575-2585 (2016).
21. Bradley Ellert, Stephen Makonin, Fred Popowich.
    Appliance Water Disaggregation via Non-Intrusive Load Monitoring (NILM).
    Proceedings of the EAI International Conference on Big Data and Analytics for Smart Cities (BigDASC), 2015.
22. Stephen Makonin, Fred Popowich.
    Nonintrusive Load Monitoring (NILM) Performance Evaluation.
    Energy Efficiency, vol. 8, no. 4, pp. 809–814 (2015).
23. Stephen Makonin.
    Real-Time Embedded Low-Frequency Load Disaggregation.
    PhD Thesis, Simon Fraser University, School of Computing Science, 2014.
24. Stephen Makonin, Ivan V. Bajic, Fred Popowich.
    Efficient Sparse Matrix Processing for Nonintrusive Load Monitoring (NILM).
    Proceedings of the 2nd International Workshop on Non-Intrusive Load Monitoring, 2014.
25. Stephen Makonin, Laura Guzman Flores, Robyn Gill, Roger Alex Clapp, Lyn Bartram, Bob Gill.
    A Consumer Bill of Rights for Energy Conservation.
    Proceedings of the IEEE Canada International Humanitarian Technology Conference (IHTC), 2014.
26. Stephen Makonin
    Nonintrusive Load Monitoring (NILM): What an algorithm can tell you about your energy consumption.
    In Poster Session at SFU Postdoctoral Research Day, 2016.
    In Poster Session at IEEE Vancouver Section Annual General Meeting, 2014.
    
27. Stephen Makonin, William Sung, Ryan Dela Cruz, Brett Yarrow, Bob Gill, Fred Popowich, Ivan V. Bajic.
    Inspiring Energy Conservation Through Open Source Metering Hardware and Embedded Real-Time Load Disaggregation.
    Proceedings of the 5th IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC), 2013.
28. Stephen Makonin, Fred Popowich, Bob Gill.
    The Cognitive Power Meter: Looking Beyond the Smart Meter.
    Proceedings of the 26th Annual IEEE Canadian Conference on Electrical and Computer Engineering (CCECE), 2013.
29. Stephen Makonin.
    Approaches to Non-Intrusive Load Monitoring (NILM) in the Home.
    PhD depth report, Simon Fraser University, School of Computing Science, 2012.

Data Engineering, Public Datasets & Big Data

1. Mostafa Farrokhabadi, Jethro Browell, Yi Wang, Stephen Makonin, Wencong Su, Hamidreza Zareipour.
   Day-Ahead Electricity Demand Forecasting Competition: Post-COVID Paradigm.
   IEEE Open Access Journal of Power and Energy, Early Access (2022),
2. Christoph Klemenjak, Andreas Reinhardt, Lucas Pereira, Stephen Makonin, Mario Bergés, Wilfried Elmenreich.
   Electricity Consumption Data Sets: Pitfalls and Opportunities.
   Proceedings of the 6th ACM International Conference on Systems for Energy-Efficient Built Environments, Cities, and Transportation (BuildSys), 2019.
3. Stephen Makonin.
   HUE: The Hourly Usage of Energy Dataset for Buildings in British Columbia.
   Data in Brief, vol. 23, no. 103744, pp. 1-4 (2019).
4. Stephen Makonin, Z. Jane Wang, Chris Tumpach.
   RAE: The Rainforest Automation Energy Dataset for Smart Grid Meter Data Analysis.
   Data, vol. 3, no. 1, article 7, pp. 1-9 (2018)
5. Stephen Makonin, Bradley Ellert, Ivan V. Bajic, Fred Popowich.
   Electricity, water, and natural gas consumption of a residential house in Canada from 2012 to 2014.
   Scientific Data, vol. 3, no. 160037, pp. 1-12 (2016).
6. Stephen Makonin, Fred Popowich, Lyn Bartram, Bob Gill, Ivan V. Bajic.
   AMPds: A Public Dataset for Load Disaggregation and Eco-Feedback Research.
   Proceedings of the 2013 IEEE Electrical Power and Energy Conference (EPEC), 2013.
7. Stephen Makonin.
   ODDs: Occupancy Detection Dataset.
   Harvard Dataverse, V1, 2010.

Software Engineering, incl. ECE \amp; ICT

1. Stephen Makonin, Laura U. Marks, Radek Przedpelski, Alejandro Rodriguez-Silva, Ramy ElMallah.
   Calculating the Carbon Footprint of Streaming Media: Beyond the Myth of Efficiency.
   Proceedings of LIMITS 2022, Eighth Workshop on Computing within Limits, 2022.
2. Stephen Makonin.
   Start-Up Creation: The Smart Eco-Efficient Built Environment.
   Editors: Fernando Pacheco-Torgal, Erik Rasmussen, Claes-Goran Granqvist, Volodymyr Ivanov, Arturas Kaklauskas, Stephen Makonin.
   1st Ed. Woodhead Publishing, ISBN: 978-0-08-100546-0 (hardcover), 978-0-08-100549-1 (ebook), 2016.
   2st Ed. Woodhead Publishing, ISBN: 978-0-12-819946-6 (paperback), 978-0-12-819947-3 (ebook), 2020.
3. Laura Guzman, Stephen Makonin, Roger Alex Clapp.
   CarbonKit: Designing A Personal Carbon Tracking Platform.
   Proceedings of SocialSense ’19: Fourth International Workshop on Social Sensing, pp. 24-29, 2019.
4. Joanna Wallace, Kyle Richardson, Bob Gill, Stephen Makonin.
   Cognitive Radio Technology: System Evolution.
   Proceedings of the 4th International Conference On Wireless Networks and Embedded Systems (WECON), 2015.
5. Reza Filsoof, Alison Bodine, Bob Gill, Stephen Makonin, Robert Nicholson.
   Transmitting Patient Vitals Over a Reliable ZigBee Mesh Network.
   Proceedings of the IEEE Canada International Humanitarian Technology Conference (IHTC), 2014.
6. David Bennett, Stephen Makonin, Vincent W. Mayfield, Ted Neustaedter, Mark R. Wrenn.
   Visual C++ 5.0 Developer's Guide.
   Sams Publishing, ISBN: 978-0-672-31031-7, 1996.

Visualization & Human-Computer Interaction (HCI)

1. Stephen Makonin, Daniel McVeigh, Wolfgang Stuerzlinger, Khoa Tran, Fred Popowich.
   Mixed-Initiative for Big Data: The Intersection of Human + Visual Analytics + Prediction.
   Proceedings of the 49th Hawaii International Conference on System Sciences (HICSS), pp. 1427-1436, 2016.
2. Stephen Makonin, Lyn Bartram, Fred Popowich.
   A Smarter Smart Home: Case Studies of Ambient Intelligence.
   IEEE Pervasive Computing, vol. 12, no. 1, pp. 58–66 (2013).
3. Stephen Makonin, Fred Popowich, TaeJin Moon, Bob Gill.
   Inspiring Energy Conservation Through Open Source Power Monitoring and In-Home Display.
   Proceedings of the IEEE Power and Energy Society General Meeting, 2013.
4. Stephen Makonin, Fred Popowich.
   Home Occupancy Agent: Occupancy and Sleep Detection.
   GSTF Journal on Computing, vol. 2, no. 1, pp. 182–186 (2012).
5. Stephen Makonin, Maryam H. Kashani, Lyn Bartram.
   The Affect of Lifestyle Factors on Eco-Visualization Design.
   Proceedings of Computer Graphics International (CGI), 2012.
6. Stephen Makonin, Philippe Pasquier, Lyn Bartram.
   Elements of Consumption: An abstract visualization of household consumption.
   Proceedings of the 11th International Symposium on Smart Graphics, LNSC 6815:194–198, 2011.
7. Stephen Makonin, Fred Popowich.
   An intelligent agent for determining home occupancy using power monitors and light sensors.
   Proceedings of the 9th International Conference on Smart Homes and Health Telematics (ICOST), LNSC 6719:236–240, 2011.

Academic Exploits

Current Supervision

• Maria Tu — MASc Thesis (Senior Supervisor, Jan/2021 to present)
  Thesis: tbd (subject area: NILM, Modelling, Data and Software Engineering)
  

Past Supervision

• Md. Zulfiquar Ali Bhotto — Postdoctoral Fellow (Co-Supervisor, Dec/2017 to Dec/2021)
  Research subject area: Adaptive Filters, Optimization, Machine Learning, Power Grid
  
• Alejandro Rodriguez-Silva — MASc Thesis (Senior Supervisor, Jan/2018 to Dec/2021)
  Thesis: Filtering in Non-Intrusive Load Monitoring
  
• Richard Jones — MASc Thesis (Senior Supervisor, May/2019 to Dec/2020)
  Thesis: Non-Parametric Modeling in Non-Intrusive Load Monitoring
  Awards: GDES Entrance Scholarship, NSERC CGS-M
  
• Alon Harell — MASc Thesis (Co-Supervisor, May/2018 to Aug/2020)
  Thesis: Deep Learning Applications in Non-Intrusive Load Monitoring
  Awards: NSERC CGS-M
  
• Bradley Ellert — MSc Thesis (Co-Supervisor, defended Aug 17, 2015)
  Thesis: Leveraging Submetered Electricity Loads to Disaggregate Household Water-Use

Visiting Scholars

• Keke Li (李可可) — Visiting Masters Scholar from Northeastern University, China (Sep/2020 to now, virtual)
  
• David Murray — Visiting PhD Scholar from University of Strathclyde, UK (Jul/2019 to Aug/2019, 2 months)
  
• Bundit Buddhahai — Visiting PhD Scholar from KMUTT, Thailand (May/2019 to Oct/2019, 6 months)
  
• Christoph Klemenjak — Visiting PhD Scholar from University of Klagenfurt, Austria (May/2019 to Aug/2019, 3 months)
  
• Shikha Singh — Visiting PhD Scholar from IIIT-Delhi, India (Jul/2018, ½ month)
  Grant: IC-IMPACTS NCE and India DST
• Megha Gaur — Visiting PhD Scholar from IIIT-Delhi, India (Sep/2017 to Feb/2018, 6 months)
  Grant: IC-IMPACTS NCE and India DST

Research Grants [PI = Principal Investigator]

• Co-Principal Investigator — SSHRC Knowledge Synthesis Grant ($50,000 over 1 year), 2020
  Title: Tackling the Carbon Footprint of Streaming Media
• Principal Investigator — NSERC Engage Grant ($25,000 over 6 months), 2019
  Title: Inferring power grid transformer to meter association using inconsistent geospatial data
• Investigator — European Commission Horizon2020 Grant (2 years)
  Title: SENSors and Intelligence in BuLt Environment (SENSIBLE) project
  [indirect moneys to allow for grad student visits]
• Principal Investigator — NSERC Discovery Launch Supplement Award ($12,500), 2019
• Principal Investigator — NSERC Discovery Grant ($140,000 over 5 years), 2018
  Title: Non-Intrusive Load Monitoring
• Postdoc — IC-IMPACTS NCE Project Grant ($133,000, 2 years, 11.2% success rate)
  Title: Energy and Water Disaggregation for Non-Intrusive Load Monitoring in Buildings
  [I was a main author and organizer of grant but could not be co-PI due to funding rules]
• PhD Candidate — SFU GSS Professional Development Grant ($500), 2014
• Principal Investigator — BCIT School of Energy Research Seed Funding ($10,000 over 4 months), 2013
  Title: Branch Circuit Ammeter and Data Logger for Smart Grid/Home Application
• PhD Candidate — SFU GSS Professional Development Grant ($500), 2012

Course Instruction

• SFU Data Fellowships - A series of short, part-time courses that offers foundational data science and AI concepts.
  Simon Fraser University, SFU'S Big Data Hub: 2021 (Feb/Apr/Jun/Oct)
• CMPT 165 - Introduction to the Internet and the World Wide Web
  Simon Fraser University, School of Computing Science: Fall/2014, Spring/2015.

Awards & Achievements

Service To Profession

Advisory Boards/Committees

• Advisory Board Member, IEEE DataPort, 2020 — now
• Faculty Advisory Member, SFU Sustainability Advisory Council (S-AC), 2021 — now

Journal Editorship

• Editor in Chief, Metadata Review Board,IEEE DataPort, 2020 — now
• Editorial Board Member, Scientific Data, Nature, 2019 — now
• Guest Editorial Board Member, Open Access Journal of Power and Energy,IEEE, 2021 — now
  Special Section: COVID-19 Impact on Electrical Grid Operation: Analysis and Mitigation

Standards Associations

• Voting Member, Big Data Governance and Metadata Management (IEEE P2957 BDGMMWG)
  Chiar, Implementation Testbed Subgroup
  IEEE Standards Association (IEEE SA) & NIST (USA)

General Chair/Co-Chair & Organizer

• 5th International Workshop on Non-Intrusive Load Monitoring (NILM), Yokohama Japan, 2020
• Advanced Signal Processing for Non-intrusive Load Monitoring Special Session at ICASSP, Brighton UK, 2019
• 4th International Workshop on Non-Intrusive Load Monitoring (NILM), Austin USA, 2018
• The Plenty of Fish (POF) 24hr Hackathon, Vancouver Canada, 2017
• 3rd International Workshop on Non-Intrusive Load Monitoring (NILM), Vancouver Canada, 2016
• IEEE Vancouver Windows 10 Hackathon (28-hours), Vancouver Canada, 2015
• IEEE Vancouver Kinect and Structure Sensor Hackathon (28-hours), Vancouver Canada, 2014

Website & Social Media Chair

• 14th IEEE International NEW Circuits And Systems (NEWCAS) Conference, 2016
• 29th Annual IEEE Canadian Conference on Electrical and Computer Engineering (CCECE), 2016
• IEEE 15th International Conference on High Performance Switching and Routing (HPSR), 2014

Local Arrangements Chair

• IEEE 20th International Workshop on Multimedia Signal Processing (MMSP), 2018
• IEEE World Congress on Computational Intelligence (WCCI), 2016

Technical Program Committee

• eSim 2020 Conference, International Building Performance Simulation Association (IBPSA-Canada): 2020
• 11th IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC): 2019
• 5th IFIP Conference on Sustainable Internet and ICT for Sustainability (SustainIT): 2017
• IEEE Workshop on Pervasive Energy Services (PerEnergy): 2015, 2016, 2017
• 3rd International Workshop on Computational Energy Management in Smart Grids (CEMiSG): 2016
• EAI International Conference on Big Data and Analytics for Smart Cities (BigDASC): 2015
• International Conference on Ubiquitous Computing & Ambient Intelligence (UCAmI): 2011—2015
• IEEE International Conference on Power and Energy (PECON): 2012

Software Engineering Services

Long before he completed his graduate studies, Dr. Makonin founded his professions consulting company in 1996. Since then, he has earned prestige for its development of complex billing, manufacturing and customer care systems and its streamlining of mass dynamic data and legacy system conversions. Highly regarded as an expert architect of high-speed data conversion tools and processing utilities, Dr. Makonin is also respected for his research scientist, project management, data engineering, and software engineering skills; this includes technical writing and editing. An ability to master emerging languages and technologies on the fly gives him the edge in today's fast-paced work environments.

Dr. Makonin is proud of his reputation and continues to build upon that reputation by supplying distinctive, quality components, libraries, and applications. HE has provided quality solutions and is committed to excellence and customer satisfaction. His innovative solutions are: constructed to ease the burden of unwieldy administration; developed using the latest, progressive technology; as dynamic-looking as they are functional; designed for 99% uptime on mission-critical applications; reliable and secure; fully documented; and cost-effective.

Full SDLC Services for Application and Web Development including:

• Conceptual Phase — preliminary evaluation including feasibility studies and preliminary risk assessments;
• Definition Phase — definition of requisite resources, time cost and performance estimates;
• Production Phase — building the end product including support documentation;
• Operation Phase — integration of the end product into the organizational environment; and,
• Divestment Phase — reallocation of resources and post-implementation evaluation.

Application Design and Development including:

Development and design of components, databases, applications, tools and internet features including but not limited to:

• audits and authentication of user logins;
• batch programs to FTP and email files to and from the server;
• batch programs to streamline databases;
• billing and bill inquiry systems including internet billing, auto-billing mailouts, billing engines, and built-in secure encryption modules;
• conversions (database to server, binary switch data to ASCII records, legacy systems to client-server);
• customer care systems;
• data maintenance applications;
• database synchronization applications;
• high-speed data conversion tools;
• interactive games;
• libraries to import address book formats into the mail system;
• mail activity logs including reports detailing usage statistics;
• mass dynamic data conversion;
• n-tier solutions;
• objects, screens and screen prototypes;
• optimized database access to eliminate speed issues;
• processing utilities;
• promotions and new service offerings;
• returned merchandise authorization;
• test utilities to simulate user load on servers;
• utilities to resolve binary compatibility issues or to compile projects;
• validation and/or formatting of data; and,
• workflows to automate communication and eliminate paperwork.

Internet Development including:

• Creation of internet calendars for internal and/or external organizations;
• Development of internetwork order tracking systems that can be easily utilized by employees;
• Building of intranets containing contact information and valuable features specific to the client environment;
• Setup of newsgroups to facilitate workplace discussions;
• Design of screens for any web-based application;
• Hosting setup and enhancement of internet access capabilities;
• Design of websites for data querying and server/scheduler configuration;
• User and affiliate sign up utilities; and,
• Modification of current websites or site construction from scratch.